This compared to the overall increase in compensation of 14% in last year’s report.
The Burtch Works Study is based on compensation and demographic data for 374 data scientists collected in interviews conducted by Burtch’s recruiting staff during the 12 months ending March 2016. It focuses on data scientists as distinguished from other analytics professionals, defining them as follows:
Data scientists apply sophisticated quantitative and computer science skills to both structure and analyze massive unstructured datasets or continuously streaming data, with the intent to derive insights and prescribe action. The depth and breadth of their coding skills distinguishes them from other predictive analytics professionals and allows them to exploit data regardless of its source, size, or format. Through the use of one or more general-purpose coding languages and data infrastructures, data scientists can tackle problems made very difficult by the size and disorganization of the data.
Here are the highlights of the new report:
- Individual contributors: Median base salaries range from $97,000 at level 1 to $152,000 at level 3 plus bonuses ranging from $10,000 to $21,000 (over 73% of all individual contributors are eligible for bonuses).
- Managers: Median base salaries range from $140,000 at level 1 to $240,000 at level 3 plus bonuses ranging from $15,000 to $80,000 (over 80% of managers are eligible for bonuses).
- Salary changes from last year’s study: Base salaries for individual contributors have increased 7% at level 1 and 1% at level 3, while salaries remained steady at level 2. For managers, salaries remained steady at level 1 while those at level 2 increased 3%. At level 3, the median base salary decreased by 4% ($10,000).
- Data scientists continue to get top compensation for analytics professionals: Data scientists earn base salaries up to 39% higher than other predictive analytics professionals depending on job category.
- A shift in the educational background of data scientists: 59% of level 1 individual contributors’ highest degree is a Master’s, a significant increase from last year’s 48%.
- An increase in the number of U.S. citizens in the data science talent pool: Among level 1 individual contributors, only 43% of this year’s professionals are foreign-born vs. 53% last year.
It appears that the increase in the number of graduate-level programs in data science has started to make its mark and is contributing to an increase in the supply of entry-level data scientists with a Master’s degree. Other trends Burtch Works has observed in its recent conversations with data scientists are increased desire to work for “more mission-driven organizations attempting to make an impact on society” rather than large companies such as Facebook or Google and “the increasing pressure on many startups to show their value,” otherwise known as the coming burst of the Unicorn Bubble.
If we do see a contraction in startup activity and attractiveness over the next year, it may well be that larger and more stable companies, even in traditional industries, will become more desirable for budding—and even experienced—data scientists, regardless of their desire to “change the world.” The job opportunities—and the high compensation—will certainly be there as the practice of data science spreads into all corners of the economy. As Burtch Works predicts: “The use of data science will become more ubiquitous, the talent supply will improve, and there will be even more use cases for these techniques.”
This article was originally published on Forbes.com and was republished on the Attunity blog with permission from the author.
About the Author
Gil Press is the Managing Partner at gPress, a marketing, publishing, research and education consultancy. Prior to gPress, he held senior marketing and research management positions at NORC, DEC and EMC. Most recently, he was Senior Director, Thought Leadership Marketing at EMC, where he launched the Big Data conversation with the “How Much Information?” study (2000 with UC Berkeley) and the Digital Universe study (2007 with IDC). Gil is a regular contributor to Forbes and he blogs on his own sites: What’s the Big Data? And The Story of Information. He can be found on Twitter at: @GilPress.